Multi‐model assessment of sub‐seasonal predictive skill for year‐round Atlantic–European weather regimes

Abstract

The prediction skill of sub‐seasonal forecast models is evaluated for seven year‐round weather regimes in the Atlantic–European region. Reforecasts based on models from three prediction centers are considered and verified against weather regimes obtained from ERA‐Interim reanalysis. Results show that predicting weather regimes as a proxy for the large‐scale circulation outperforms the prediction of raw geopotential height. Greenland blocking tends to have the longest year‐round skill horizon for all three models, especially in winter. On the other hand, the skill is lowest for the European blocking regime for all three models, followed by the Scandinavian blocking regime. Furthermore, all models struggle to forecast flow situations that cannot be assigned to a weather regime (so‐called no regime), in comparison with weather regimes. Related to this, variability in the occurrence of no regime, which is most frequent in the transition seasons, partly explains the predictability gap between transition seasons and winter and summer. We also show that models have difficulties in discriminating between related regimes. This can lead to misassignments in the predicted regime during flow situations in which related regimes manifest. Finally, we document the changes in skill between model versions, showing important improvements for the ECMWF and NCEP models. This study is the first multi‐model assessment of year‐round weather regimes in the Atlantic–European domain. It advances our understanding of the predictive skill for weather regimes, reveals strengths and weaknesses of each model, and thus increases our confidence in the forecasts and their usefulness for decision‐making.

Literature survey of subseasonal‐to‐seasonal predictions in the southern hemisphere

“…Looking at the number of S2S studies on the SH, there is a need to conduct more studies for the SH, particularly for the African continent. In fact, there are very few applications S2S prediction studies compared to seasonal prediction studies in both hemispheres (Osman et al, 2023). The African continent is vulnerable to weather‐ and climate‐related disasters, and S2S forecasts can assist in alleviating the risk of such disasters.…”

Flow‐Dependence of Ensemble Spread of Subseasonal Forecasts Explored via North Atlantic‐European Weather Regimes

“…The weather regime definition is based on 6-hourly 500-hPa geopotential height anomalies (Z500′) from ERA5 reanalysis (Hersbach et al, 2020) at 0.5°horizontal resolution. Z500′ are normalized with the spatially averaged 30-day running standard deviation at a given calendar time, to remove seasonal variability in Z500′ amplitude (see Osman et al, 2023). Then, a k-means clustering in the phase space spanned by the leading seven EOFs of 10-day low-pass filtered, normalized Z500′ is performed.…”

“…Dates when none of the IWR values meet this definition are categorized as "no regime". Weather regimes were computed for ECMWF S2S forecasts (model cycles CY46R1 and CY47R1) following the approach outlined in Osman et al (2023). However, these forecasts are mapped onto weather regimes identified using ERA5 reanalysis data.…”

Why Moist Dynamic Processes Matter for the Sub‐Seasonal Prediction of Atmospheric Blocking Over Europe

“…We focus on EuBL onsets in different pentads (lead times of 0-4 days, 5-9 days, 10-14 days, and 15-19 days) since forecast skill for Atlantic-European weather regimes and WCBs on average vanishes in week 2 (7-14 days) (Büeler et al, 2021;Osman et al, 2023;Wandel et al, 2021). Onsets of large-scale and persistent flow regimes at lead times of 5-20 days are of particular interest from a sub-seasonal prediction perspective, because, due to their persistence, they strongly influence the circulation even beyond lead times of 20 days.…”